Results 71 to 80 of about 1,873 (195)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

MLDAS: Machine Learning Dynamic Algorithm Selection for Software‐Defined Networking Security

Concurrency and Computation: Practice and Experience, Volume 38, Issue 5, March 2026.
ABSTRACT Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML) algorithms with Software‐Defined Networking (SDN) controllers to enhance network security through adaptive ...
Pablo Benlloch, Oscar Romero, Antonio Leon, Jaime Lloret   +3 more
wiley   +1 more source

Robust Classification of Encrypted Network Services Using Convolutional Neural Networks Optimized by Information Bottleneck Method

IEEE Access
The rapid growth of encrypted network traffic poses significant challenges for network monitoring and security systems, as traditional methods often fail to accurately classify encrypted services.
Zhijiong Wang, Wei Lin, Yu Chen, Mang I. Vai   +3 more
doaj   +1 more source

High‐Resolution Neural Network‐Based Teaching Skill Development for Teachers in Edge Computing Environment

Engineering Reports, Volume 8, Issue 3, March 2026.
Where user devices include cell phones, tablets, laptops, and so on, which communicate with edge computing servers and use computational as well as storage resources provided by edge computing. Network connectivity is the core component of edge computing, which allows communication between mobile devices and edge computing nodes.
Genlian Zhang
wiley   +1 more source

HADA: A Hybrid Anomaly Detection Approach Using Unsupervised Machine Learning

Engineering Reports, Volume 8, Issue 3, March 2026.
Overview of HADA, an unsupervised fraud detection pipeline that preprocesses and scales transaction data, applies PCA for dimensionality reduction, scores anomalies using Isolation Forest, selects anomalous transactions via thresholding, and clusters the selected anomalies using Agglomerative Hierarchical Clustering (AHC) to produce interpretable ...
Francis Thiong'o, Lawrence Nderu, Ronald Waweru Mwangi, Isaac Nyabisa Oteyo   +3 more
wiley   +1 more source

Encrypted malicious traffic detection based on neural network

Dianzi Jishu Yingyong
With the widespread application of encrypted communications, traditional malicious traffic detection methods based on content analysis have gradually become ineffective.
Xia Longfei, Zhang Qihao, Wu Xianyun, Zhu Xuetian, Gu Xin, Tian Min   +5 more
doaj   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, Volume 14, Issue 3, Page 1431-1455, March 2026.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

A Hybrid Encryption Framework for Secure and Real‐Time Vehicular Communications

SECURITY AND PRIVACY, Volume 9, Issue 2, March/April 2026.
ABSTRACT The rapid expansion of Vehicular Ad Hoc Networks (VANETs) has amplified concerns regarding data security, integrity, and privacy. This paper presents SECURIDE, a Secure Intelligent Data Exchange for Connected Vehicles that provides a comprehensive encryption–decryption framework for safeguarding multimedia data and communication channels in ...
Muhammad Usama, Muhammad Usman Hadi
wiley   +1 more source

Encrypted traffic classification method based on parallel traffic graph and graph neural network

Tongxin xuebao
Aiming at the problems of traditional encrypted traffic classification methods limited by the imbalance of dataset classes and the unreliability of the features used in complex network environments, an encrypted traffic classification method based on ...
LIU Taotao, FU Yu, YU Yihan, AN Yishuai
doaj  

CLA-BERT: A Hybrid Model for Accurate Encrypted Traffic Classification by Combining Packet and Byte-Level Features

Mathematics
Encrypted traffic classification is crucial for network security and management, enabling applications like QoS control and malware detection. However, the emergence of new encryption protocols, particularly TLS 1.3, poses challenges for traditional ...
Hong Huang, Yinghang Zhou, Feng Jiang
doaj   +1 more source